Time series and fractal analyses of wheezing: a novel approach
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SCIENTIFIC PAPER
Time series and fractal analyses of wheezing: a novel approach M. S. Swapna1 · A. Renjini1 · Vimal Raj1 · S. Sreejyothi1 · S. Sankararaman1 Received: 17 June 2020 / Accepted: 7 October 2020 © Australasian College of Physical Scientists and Engineers in Medicine 2020
Abstract Since the outbreak of the pandemic Coronavirus Disease 2019, the world is in search of novel non-invasive methods for safer and early detection of lung diseases. The pulmonary pathological symptoms reflected through the lung sound opens a possibility of detection through auscultation and of employing spectral, fractal, nonlinear time series and principal component analyses. Thirty-five signals of vesicular and expiratory wheezing breath sound, subjected to spectral analyses shows a clear distinction in terms of time duration, intensity, and the number of frequency components. An investigation of the dynamics of air molecules during respiration using phase portrait, Lyapunov exponent, sample entropy, fractal dimension, and Hurst exponent helps in understanding the degree of complexity arising due to the presence of mucus secretions and constrictions in the respiratory airways. The feature extraction of the power spectral density data and the application of principal component analysis helps in distinguishing vesicular and expiratory wheezing and thereby, giving a ray of hope in accomplishing an early detection of pulmonary diseases through sound signal analysis. Keywords Auscultation · Wheeze · Fractals · Nonlinear time series analysis · Sample entropy
Introduction Respiratory diseases are one among the leading cause of deaths in the world, which is usually diagnosed through auscultation. Based on the frequency, intensity, time duration, and quality of the sound, a pathological and healthynormal breath signal can be distinguished [1–3]. When the normal lung sounds are generated due to the movement of air through the tracheobronchial tree, the vibrations of solid tissues, are responsible for the adventitious or abnormal lung sounds. In the normal lung sounds, the vesicular sounds (VS) are heard over the chest wall distant from larger airways. Adventitious sounds can be generally classified as continuous and discontinuous based on their duration of occurrence. When the continuous adventitious breath sounds (wheezes, stridor, and rhonchi are musical) exhibit a time duration of > 250 ms, the discontinuous adventitious signals show a time duration of
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